Noncontrast Computed Tomography Markers Associated with Hematoma Expansion: Analysis of a Multicenter Retrospective Study

Background: Hematoma expansion (HE) is a significant predictor of poor outcomes in patients with intracerebral hemorrhage (ICH). Non-contrast computed tomography (NCCT) markers in ICH are promising predictors of HE. We aimed to determine the association of the NCCT markers with HE by using different temporal HE definitions. Methods: We utilized Risa-MIS-ICH trial data (risk stratification and minimally invasive surgery in acute intracerebral hemorrhage). We defined four HE types based on the time to baseline CT (BCT) and the time to follow-up CT (FCT). Hematoma volume was measured by software with a semi-automatic edge detection tool. HE was defined as a follow-up CT hematoma volume increase of >6 mL or a 33% hematoma volume increase relative to the baseline CT. Multivariable regression analyses were used to determine the HE parameters. The prediction potential of indicators for HE was evaluated using receiver-operating characteristic analysis. Results: The study enrolled 158 patients in total. The time to baseline CT was independently associated with HE in one type (odds ratio (OR) 0.234, 95% confidence interval (CI) 0.077–0.712, p = 0.011), and the blend sign was independently associated with HE in two types (OR, 6.203–6.985, both p < 0.05). Heterogeneous density was independently associated with HE in all types (OR, 6.465–88.445, all p < 0.05) and was the optimal type for prediction, with an area under the curve of 0.674 (p = 0.004), a sensitivity of 38.9%, and specificity of 96.0%. Conclusion: In specific subtypes, the time to baseline CT, blend sign, and heterogeneous density were independently associated with HE. The association between NCCT markers and HE is influenced by the temporal definition of HE. Heterogeneous density is a stable and robust predictor of HE in different subtypes of hematoma expansion.


Introduction
Acute spontaneous cerebral hemorrhage is the most severe and incurable type of stroke, with one-third of patients dying within the first month [1]. Hematoma expansion (HE) is a strong predictor of poor outcomes in patients with intracerebral hemorrhage (ICH) [2][3][4]. Markers that are predictive of HE can help in selecting patients for hemostatic treatment [5]. Therefore, the early identification of patients at high risk of HE is critical. The spot sign on computed tomographic angiography (CTA) has been shown to have a high predictive value for increased hematoma [5][6][7][8][9].
Furthermore, leakage and iodine signs are also sensitive predictors of HE [10,11]. However, in some countries and regions, the low popularity rate of CTA limits the use of these markers. In contrast to CTA, non-contrast computed tomography (NCCT) markers have the potential to be a low-cost and widely used tool for cerebral hemorrhage risk stratification [12]. NCCT markers can be classified as density and shape markers [13]. Swirl signs, heterogeneous density, black hole signs, blend signs, and blood-fluid levels are widely used as qualitative hematoma heterogeneity markers to predict HE [14][15][16][17][18]. Currently, there is no standardized definition of HE, and the relationship between predictors and HE varies according to different volume growth definitions of HE [16,[19][20][21]. However, there is a lack of studies examining the relationship between predictors and HE under different temporal definitions. Consequently, we sought to determine the associations between NCCT markers and hematoma expansion under various temporal definitions and to identify stable markers for predicting hematoma expansion.

Study Design and Subjects
Our study is based on the Risa-MIS-ICH trial retrospective study database (Clinical Trials Identifier: NCT03862729, https://www.clinicaltrials.gov, accessed on 1 December 2021). As of November 2021, the retrospective study had enrolled 1040 patients with spontaneous supratentorial cerebral hemorrhage and 225 patients with time to baseline CT within 12 h and a follow-up CT within 72 h. The time to baseline CT (BCT) was defined as the time from symptom onset to CT scan immediately after admission to the hospital. The exclusion criteria were as follows: (1) the CT was not NCCT at baseline; (2) the surgical intervention was conducted before the follow-up CT; and (3) the CT image quality was not optimal. The Ethics Committee at Fujian Medical University's First Affiliated Hospital approved the study (Ethical Approval Number: MRCTA, ECFAH of FMU [2018] 082-1).

Treatment
The patients in this study were treated according to the following two guidelines: Guidelines for the Management of Spontaneous Intracerebral Hemorrhage: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association (2015) [22] and Chinese multidisciplinary expert consensus: Diagnosis and Treatment of Spontaneous Cerebral Hemorrhage (2015).

Imaging Evaluation
Admission and follow-up NCCT scans were obtained according to the standard clinical protocols with axial 5-mm section thickness. The swirl sign, black hole sign, blend sign, blood-fluid level, and ultraearly hematoma growth (uHG) are defined based on the previous literature [3,[13][14][15][16][17][18]. Heterogeneous density is defined as at least three foci of hypoattenuation compared to the surrounding hematoma, as assessed on the axial NCCT slice with the most ICH. (Barras density scale = III, IV, or V) [16]. Supplementary Figure S1 shows images of several representative NCCT markers. Brainlab iPlan CMF 3.0 software (Brainlab, Heimstetten, Germany) assessed the volume of the hematoma using semi-automatic edge detection technology. Two experienced neurosurgeons independently reviewed all images and evaluated the presence or absence of various NCCT markers based strictly on the definitions. They were unaware of clinical information about the patient before the imaging evaluation. A reviewer was added to the panel in case of discrepancies, and the three resolved the issue by consensus. According to commonly used growth criteria, hematoma expansion was defined as an absolute growth volume of more than 6 mL or a relative growth of more than 33% [5,[23][24][25]. Four types of hematoma growth were defined according to BCT < 6 or 12 h and FCT < 24 or 72 h.

Statistical Analysis
SPSS version 27.0 (SPSS Inc., Chicago, IL, USA) and MedCalc software (MedCalc 20.0, MedCalc, Mariakerke, Belgium) were used for the analysis. A two-tailed Student's t-test was used to compare the continuous variables with a normal distribution reported as the mean (SD). Continuous variables with non-normal distributions were represented by the median (25th-75th quartile) and analyzed using the Mann-Whitney U test. Categorical variables were expressed as numbers (%), and distribution differences between groups were determined using the chi-square test or Fisher's test. We used univariate analysis to find potential essential factors that could influence HE. Elements with p < 0.05 in the univariate analysis were forced into the multiple regression model, adjusting for potential predictors of p < 0.05 in other types. Receiver-operating characteristic curves were drawn to assess independent predictors for predicting HE. The inter-rater and intra-rater reliability was calculated through the intraclass correlation coefficient (ICC) in the measurement of hematoma volume. For an ICC, moderate agreement was considered as 0.41 to 0.60, substantial agreement as 0.61 to 0.80, and excellent as 0.81 to 1.00. All tests were 2-tailed, and p < 0.05 was considered statistically significant.

Characteristics of Study Patients
A total of 158 ICH patients were included in this study and were divided into four types according to different CT time definitions (Supplementary Figure S2)

Independent Predictive Value of Significant Predictors for HE
The receiver-operating characteristic (ROC) curve analysis revealed that the area under the curve (AUC) of the heterogeneous type was 0.674 (p = 0.004) and the time to baseline CT was 0.715 (p = 0.001) for the type with BCT within 6 h and FCT within 24 h (Figure 1). The heterogeneity was 0.638 (p = 0.005) and the blend sign was 0.618 (p = 0.012) in the type with BCT within 6 h and FCT within 72 h (Figure 1). The heterogeneity was 0.660 (p = 0.003) in the type with BCT within 12 h and FCT within 24 h; meanwhile, the heterogeneity was 0.638 (p = 0.002) and the blend sign was 0.613 (p = 0.005) in the type with BCT within 12 and FCT within 72 h (Figure 1). "Heterogeneous" demonstrates consistently sound predictive value for any definition, predicting HE with sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve, as detailed in Table 7. Table 7. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve of hematoma heterogeneity to predict hematoma expansion in different types. sound predictive value for any definition, predicting HE with sensitivity, specificity, itive predictive value, negative predictive value, and area under the curve, as detaile Table 7.

Discussion
Our study showed that heterogeneous hematoma was independently associated with the risk of hematoma expansion. However, the association of other predictors with hematoma expansion varies depending on each definition of HE. The blend sign was independently associated with HE in half of the descriptions, while time to baseline CT was independently associated with HE in only 25% of the definitions.
No standard definition of hematoma expansion is currently available. Reports on hematoma expansion refer to the increase in volume and the corresponding time. In earlier studies, hematoma expansion was defined as an absolute increase of 20 mL or a relative increase of >40% [26], but this definition is now rarely used. Later, Brott et al. defined hematoma expansion as an increase in the relative volume of greater than 33% [27,28]; this definition is still used today [29,30]. Currently, hematoma expansion is mainly defined by a combination of relative and absolute growth, with >33% or >6 mL [3,9,[31][32][33][34][35] and >33% or >12.5 mL [17,36,37] being the standard; in particular, >33% or >6 mL is widely used. Different definitions of volume growth affect the relationship between predictors and HE [16,[19][20][21]. The time aspect of hematoma definitions is often ignored. Due to the relative instability of early hematomas, hematoma growth is more common among patients with early ICH. The activation of the coagulation system allows the hematoma to become progressively more stable as time passes. Consequently, a CT scan performed late after the onset of the disease may be less likely to detect an enlarged hematoma, and it is more accurate to say that the hematoma has grown to a stable state than that it has not grown. H. Bart Brouwers et al. confirmed that a shorter time to computed tomography (≤6 vs. >6 h) independently predicted HE [31], and patients with a baseline CT time < 6 h were included in a subsequent study of hematoma expansion [4,20,35]. Considering that some patients cannot reach the hospital and receive a CT scan in time, especially in remote areas, and 17% of hematoma expansion occurred 6 h after onset [38], we consider it reasonable to include baseline CT time < 12 h in the study. In addition, there is no uniformity in the definition of follow-up CT time, but it is generally within 72 h [35,39,40]. As a result, when studying the relationship between predictors and HE, the type of HE definition used should be noted.
Contrast extravasation observed on CTA is a significant indicator for identifying ongoing bleeding [5]. The spot sign is a strong predictor of HE [5]; this sign is characterized as one or more 1 to 2 mm foci of enhancement within the hematoma on CTA source pictures [6], and the enhancement foci are generally considered to be manifestations of the extravasation of the contrast medium from the blood vessels. Later, the leakage and iodine signs on CTA images were also considered risk factors for HE sensitivity [10,11]. CTA is an ideal screening technique for cerebral hemorrhage because it can detect the marker that predicts hematoma expansion and identify bleeding caused by vascular malformation. However, CTA tests are not readily accessible, limiting their extensive application in clinical practice.
In contrast to CTA, NCCT is readily available in most stroke hospitals. NCCT markers can be divided into two types based on shape and density [13,24], and NCCT markers representing hematoma density are more common than those representing shapes. NCCT markers based on hematoma density, such as the swirl sign, black hole sign, blend sign, blood-fluid level, and density category of hematoma, were described as "heterogeneous", representing local or global hematoma heterogeneity. Notably, the definition of NCCT markers is relatively complex; there is no consensus, and there is inter-reviewer variability [41]. Recent studies have shown that quantitative NCCT markers can be used to predict hematoma expansion [42,43]; however, the need for specialist software may limit the widespread use of this technique. In addition, the artificial intelligence model offers improved specificity and sensitivity in predicting HE [44]. In conclusion, predicting HE using NCCT images is a promising prospect. We recommend that all NCCT markers be prospectively validated and evaluated for inter-and intra-rater reliability.
Fisher et al. proposed an "avalanche" model to explain the mechanism of hematoma expansion [45]. In this model, the hematoma stretches the surrounding brain tissue, causing numerous small blood vessels to be cut and ruptured. As the hematoma increases further, the pressure on the surrounding brain tissue increases, and the hemorrhage stops when the hematoma and surrounding tissue pressure are balanced [16,46]. In this model, the earlier hematoma continuously adds new liquid blood until the bleeding stops. The clot shrinks after bleeding to obtain hemostasis, the serum is extruded, and the CT attenuation of the hematoma increases [47]. Fluid blood from an active hemorrhage hypoattenuates on a CT scan relative to the surrounding brain or high attenuation thrombus [46]. Thus, hematoma heterogeneity may represent the coexistence of relatively early high-attenuation hematomas with relatively new bleeding low-attenuation hematomas in active bleeding.
We speculate that, if the hematoma is slowly and continuously expanding, the further active bleeding may be of multiple origins, which may be more consistent with a heterogeneous density score. This type of hematoma expansion is probably the most common. However, if there is active bleeding on top of a relatively stable hematoma, i.e., if there are two peaks of bleeding, this may be more consistent with blend sign.
This study has several limitations. First, the sample size was relatively small. Second, the study was retrospective and had all the typical constraints of a retrospective analysis. Third, all of the definitions utilized herein commonly used growth volume (>6 mL or 33%), which may limit the applicability of our results. Fourth, patients with more than 12 h between onset and the initial CT scan were excluded from this study; therefore, our results may not apply to this population. Fifth, this was an NCCT-based study that did not compare NCCT markers to the CTA spot sign. Finally, this study only showed the association of NCCT with HE and offered no further investigation of the association of NCCT with poor outcomes, limiting the clinical value of the results.
In summary, our study showed that the time to baseline CT, blend sign, and heterogeneous density was independently associated with HE in certain subtypes. We found that different temporal HE definitions affected the relationship between predictors and HE, but heterogeneous hematoma independently predicted HE in all definition types. Heterogeneous hematoma as a stable independent predictor of HE may be a substitute when CTA scans cannot be performed, and individuals with heterogeneous hematoma may be candidates for therapy that limits early hematoma expansion. In the subsequent research, our results will be validated using prospective, multicenter, large-sample-size RIS-MIS-ICH project data.